Document Type
Article
Publication Date
11-2019
DOI
10.3389/fnhum.2019.00401
Publication Title
Frontiers in Human Neuroscience
Volume
13
Pages
401 (12 pg.)
Abstract
With the recent surge of affordable, high-performance virtual reality (VR) headsets, there is unlimited potential for applications ranging from education, to training, to entertainment, to fitness and beyond. As these interfaces continue to evolve, passive user-state monitoring can play a key role in expanding the immersive VR experience, and tracking activity for user well-being. By recording physiological signals such as the electroencephalogram (EEG) during use of a VR device, the user's interactions in the virtual environment could be adapted in real-time based on the user's cognitive state. Current VR headsets provide a logical, convenient, and unobtrusive framework for mounting EEG sensors. The present study evaluates the feasibility of passively monitoring cognitive workload via EEG while performing a classical n-back task in an interactive VR environment. Data were collected from 15 participants and the spatio-spectral EEG features were analyzed with respect to task performance. The results indicate that scalp measurements of electrical activity can effectively discriminate three workload levels, even after suppression of a co-varying high-frequency activity.
Original Publication Citation
Tremmel, C., Herff, C., Sato, T., Rechowicz, K., Yamani, Y., & Krusienski, D. J. (2019). Estimating cognitive workload in an interactive virtual reality environment using EEG. Frontiers in Human Neuroscience, 13, 401. doi:10.3389/fnhum.2019.00401
Repository Citation
Tremmel, Christoph; Herff, Christain; Sato, Tetsuya; Rechowicz, Krzysztof; Yamani, Yusuke; and Krusienski, Dean J., "Estimating Cognitive Workload in an Interactive Virtual Reality Environment Using EEG" (2019). Electrical & Computer Engineering Faculty Publications. 233.
https://digitalcommons.odu.edu/ece_fac_pubs/233
ORCID
0000-0001-8990-0010 (Yamani)
Included in
Bioelectrical and Neuroengineering Commons, Cognitive Psychology Commons, Neurosciences Commons
Comments
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.